getResults-methods {Rmagpie} | R Documentation |
This method provides an easy interface to access the results of one-layer and two-layers of cross-validation directly from an object assessment.
object |
|
layer |
|
topic |
character. Argument that specifies which kind of
result is requested, the possible values are
|
errorType |
character. Optional, ignored if topic is not |
genesType |
character. Optional, ignored if topic is not |
if there is no error, the value returned by the method depends on the arguments namely,
layer
, topic
, errorType
and genesType
.
If layer
is 1
General |
Get the results of the repeated one-layer cross-validation corresponding to
the |
if topic is |
|
If errorType= |
All the following error rates |
If errorType= |
|
If errorType= |
|
If errorType= |
numeric. Class cross-validated error rate error for each value of option tried obtained by one-layer of cross-validation (1 value per class and value of option). |
Else |
Error signaling that the topic is not appropriate. |
if topic is |
|
If genesType= |
|
Else |
Error signaling that the topic is not appropriate. |
if topic is |
Size of subset (for RFE-SVM) or threshold (for NSC) corresponding to the minimum cross-validated error rate. |
if topic is |
Time in second to perform this one-layer cross-validation. |
If layer
is c(1,i)
General |
Get the results of the ith repeat of the one-layer cross-validation corresponding to
the |
if topic is |
|
If errorType= |
All the following error rates |
If errorType= |
numeric. Cross-validated error-rate for each value of option tried obtained by one-layer of cross-validation on the ith repeat(1 value per subset). |
If errorType= |
numeric. Standard error on cross-validated error-rate for each value of option tried obtained by one-layer of cross-validation on the ith repeat (1 value per value of option). |
If errorType= |
numeric. Class cross-validated error rate error for each value of option tried obtained by one-layer of cross-validation on the ith repeat (1 value per class and value of option). |
If errorType= |
numeric. Class cross-validated error rate error for each fold and each value of option tried obtained by one-layer of cross-validation on the ith repeat (1 value per class and value of option). |
Else |
Error signaling that the topic is not appropriate. |
if topic is |
|
If genesType= |
list. Each elelement of the list corresponds to the genes selected for each model ordered by frequency. |
If genesType= |
list. Each elelement of the list corresponds to a model and contains a list of which one element correspond to the genes selected in a particular fold. |
Else |
Error signaling that the topic is not appropriate. |
if topic is |
numeric. Size of subset (for RFE) or threshold (for NSC) corresponding to the minimum cross-validated error rate in the ith repeat of the one-layer cross-validation. |
if topic is |
Time in second to perform this repeat of one-layer cross-validation. |
If layer
is 2
General |
Get the results of the repeated two-layers cross-validation corresponding to
the |
if topic is 'errorRate' |
|
If errorType= |
All the following error rates |
If errorType= |
numeric. Cross-validated error-rate obtained by two-layers of cross-validation (1 value). |
If errorType= |
numeric. Standard error on cross-validated error-rate obtained by two-layers of cross-validation (1 value). |
If errorType= |
numeric. Class cross-validated error rate obtained by two-layers (1 value per class) |
Else |
Error signaling that the topic is not appropriate. |
if topic is |
numeric. Average best number of genes for SVM-RFE of threshold for NSc obtained among the folds. |
if topic is |
Time in second to perform this two-layers cross-validation. |
If layer
is c(2,i)
General |
Get the results of the ith repeated of the two-layers cross-validation corresponding to
the |
if topic is 'errorRate' |
|
If errorType= |
All the following error rates |
If errorType= |
numeric. Cross-validated error-rate obtained by two-layers of cross-validation in this repeat. (1 value). |
If errorType= |
numeric. Standard error on cross-validated error-rate obtained by two-layers of cross-validation in this repeat (1 value). |
If errorType= |
numeric. Class cross-validated error rate obtained by two-layers in this repeat |
If errorType= |
numeric. Error rate obtained on each of the folds in the second layer in this repeat(1 value per fold). of cross-validation (value per class). |
Else |
Error signaling that the topic is not appropriate. |
if topic is |
|
If genesType= |
list. Each elelement of the list corresponds to a fold and contains a list of the genes selected in this particular fold. |
Else |
Error signaling that the topic is not appropriate. |
if topic is |
numeric. Average best number of genes obtained among the folds in this repeat. |
if topic is |
Time in second to perform this repeat of two-layers cross-validation. |
If |
This layer corresponds to the jth inner layer of one-layer cross-validation performed inside the ith repeat of the two-layers cross-validation. The returned values are similar to the one returned by a repeated one-layer cross-validation. |
If |
This layer corresponds to the kth repeat of the jth inner layer of one-layer cross-validation performed inside the ith repeat. The returned values are similar to the one returned by a repeat of one-layer cross-validation. |
The method is only applicable on objects of class assessment.
Camille Maumet
#dataPath <- file.path("C:", "Documents and Settings", "c.maumet", "My Documents", "Programmation", "Sources", "SVN", "R package", "data") #aDataset <- new("dataset", dataId="vantVeer_70", dataPath=dataPath) #aDataset <- loadData(aDataset) data('vV70genesDataset') mySubsets <- new("geneSubsets", optionValues=c(1,2,4,8,16,32,64,70)) myassessment <- new("assessment", dataset=vV70genes, noFolds1stLayer=5, noFolds2ndLayer=4, classifierName="svm", typeFoldCreation="original", svmKernel="linear", noOfRepeat=2, featureSelectionOptions=mySubsets) myassessment <- runOneLayerExtCV(myassessment) myassessment <- runTwoLayerExtCV(myassessment) # --- Access to one-layer CV --- # errorRate # 1-layer CV: error Rates getResults(myassessment, 1, 'errorRate') # 1-layer CV: error Rates - all") getResults(myassessment, 1, 'errorRate', errorType='all') # 1-layer CV: error Rates - cv getResults(myassessment, 1, 'errorRate', errorType='cv') # 1-layer CV: error Rates - se getResults(myassessment, 1, 'errorRate', errorType='se') # 1-layer CV: error Rates - class getResults(myassessment, 1, 'errorRate', errorType='class') # genesSelected # 1-layer CV: genes Selected getResults(myassessment, 1, 'genesSelected') # 1-layer CV: genes Selected - frequ getResults(myassessment, 1, 'genesSelected', genesType='frequ') # 1-layer CV: genes Selected - model 7 getResults(myassessment, 1, 'genesSelected', genesType='frequ')[[7]] getResults(myassessment, 1, 'genesSelected')[[7]] # bestOptionValue # 1-layer CV: best number of genes getResults(myassessment, 1, 'bestOptionValue') # executionTime # 1-layer CV: execution time getResults(myassessment, 1, 'executionTime') # --- Access to 2nd repeat of one-layer CV --- # Error rates # 1-layer CV repeat 2: error Rates getResults(myassessment, c(1,2), 'errorRate') # 1-layer CV repeat 2: error Rates - all getResults(myassessment, c(1,2), 'errorRate', errorType='all') # 1-layer CV repeat 2: error Rates - cv getResults(myassessment, c(1,2), 'errorRate', errorType='cv') # 1-layer CV repeat 2: error Rates - se getResults(myassessment, c(1,2), 'errorRate', errorType='se') # 1-layer CV repeat 2: error Rates - fold getResults(myassessment, c(1,2), 'errorRate', errorType='fold') # 1-layer CV repeat 2: error Rates - noSamplesPerFold getResults(myassessment, c(1,2), 'errorRate', errorType='noSamplesPerFold') # 1-layer CV repeat 2: error Rates - class getResults(myassessment, c(1,2), 'errorRate', errorType='class') # genesSelected # 1-layer CV repeat 2: genes Selected getResults(myassessment, c(1,2), 'genesSelected') # 1-layer CV repeat 2: genes Selected - frequ getResults(myassessment, c(1,2), 'genesSelected', genesType='frequ') # 1-layer CV repeat 2: genes Selected - model 7 (twice) getResults(myassessment, c(1,2), 'genesSelected', genesType='frequ')[[7]] getResults(myassessment, c(1,2), 'genesSelected')[[7]] # 1-layer CV repeat 2: genes Selected - fold getResults(myassessment, c(1,2), 'genesSelected', genesType='fold') # 1-layer CV repeat 2: best number of genes getResults(myassessment, c(1,2), 'bestOptionValue') # 1-layer CV repeat 2: execution time getResults(myassessment, c(1,2), 'executionTime') # --- Access to two-layers CV --- # Error rates # 2-layer CV: error Rates getResults(myassessment, 2, 'errorRate') # 2-layer CV: error Rates - all getResults(myassessment, 2, 'errorRate', errorType='all') # 2-layer CV: error Rates - cv getResults(myassessment, 2, 'errorRate', errorType='cv') # 2-layer CV: error Rates - se getResults(myassessment, 2, 'errorRate', errorType='se') # 2-layer CV: error Rates - class getResults(myassessment, 2, 'errorRate', errorType='class') # bestOptionValue # 2-layer CV: best number of genes (avg) getResults(myassessment, 2, 'bestOptionValue') # executionTime # 2-layer CV: execution time getResults(myassessment, 2, 'executionTime') # --- Access to two-layers CV access to repeats --- # Error rates # 2-layer CV repeat 1: error Rates getResults(myassessment, c(2,1), 'errorRate') # 2-layer CV repeat 1: error Rates - all getResults(myassessment, c(2,1), 'errorRate', errorType='all') # 2-layer CV repeat 1: error Rates - cv getResults(myassessment, c(2,1), 'errorRate', errorType='cv') # 2-layer CV repeat 1: error Rates - se getResults(myassessment, c(2,1), 'errorRate', errorType='se') # 2-layer CV repeat 1: error Rates - fold getResults(myassessment, c(2,1), 'errorRate', errorType='fold') # 2-layer CV repeat 1: error Rates - noSamplesPerFold getResults(myassessment, c(2,1), 'errorRate', errorType='noSamplesPerFold') # 2-layer CV repeat 1: error Rates - class getResults(myassessment, c(2,1), 'errorRate', errorType='class') # genesSelected # 2-layer CV repeat 1: genes Selected getResults(myassessment, c(2,1), 'genesSelected') # 2-layer CV repeat 1: genes Selected - fold getResults(myassessment, c(2,1), 'genesSelected', genesType='fold') # 2-layer CV repeat 1: best number of genes getResults(myassessment, c(2,1), 'bestOptionValue') # 2-layer CV repeat 1: execution time getResults(myassessment, c(2,1), 'executionTime') # --- Access to one-layer CV inside two-layers CV --- # errorRate # 2-layer CV repeat 1 inner layer 3: error Rates getResults(myassessment, c(2,1,3), 'errorRate') # 2-layer CV repeat 1 inner layer 3: error Rates - all getResults(myassessment, c(2,1,3), 'errorRate', errorType='all') # 2-layer CV repeat 1 inner layer 3: error Rates - cv getResults(myassessment, c(2,1,3), 'errorRate', errorType='cv') # 2-layer CV repeat 1 inner layer 3: error Rates - se getResults(myassessment, c(2,1,3), 'errorRate', errorType='se') # 2-layer CV repeat 1 inner layer 3: error Rates - class getResults(myassessment, c(2,1,3), 'errorRate', errorType='class') # genesSelected # 2-layer CV repeat 1 inner layer 3: genes Selected getResults(myassessment, c(2,1,3), 'genesSelected') # 2-layer CV repeat 1 inner layer 3: genes Selected - frequ getResults(myassessment, c(2,1,3), 'genesSelected', genesType='frequ') # 2-layer CV repeat 1 inner layer 3: genes Selected - model 7 getResults(myassessment, c(2,1,3), 'genesSelected', genesType='frequ')[[7]] getResults(myassessment, c(2,1,3), 'genesSelected')[[7]] # bestOptionValue # 2-layer CV repeat 1 inner layer 3: best number of genes getResults(myassessment, c(2,1,3), 'bestOptionValue') # executionTime # 2-layer CV repeat 1 inner layer 3: execution time getResults(myassessment, c(2,1,3), 'executionTime') # --- two-layers CV access to repeat 1, inner layer 2 repeat 2 --- # Error rates # 2-layer CV inner layer 3 repeat 2: error Rates getResults(myassessment, c(2,1,3,1), 'errorRate') # 2-layer CV repeat 1 inner layer 3 repeat 1: error Rates - all getResults(myassessment, c(2,1,3,1), 'errorRate', errorType='all') # 2-layer CV repeat 1 inner layer 3 repeat 1: error Rates - cv getResults(myassessment, c(2,1,3,1), 'errorRate', errorType='cv') # 2-layer CV repeat 1 inner layer 3 repeat 1: error Rates - se getResults(myassessment, c(2,1,3,1), 'errorRate', errorType='se') # 2-layer CV repeat 1 inner layer 3 repeat 1: error Rates - class getResults(myassessment, c(2,1,3,1), 'errorRate', errorType='class') # 2-layer CV repeat 1 inner layer 3 repeat 1: error Rates - fold getResults(myassessment, c(2,1,3,1), 'errorRate', errorType='fold') # 2-layer CV repeat 1 inner layer 3 repeat 1: error Rates - noSamplesPerFold getResults(myassessment, c(2,1,3,1), 'errorRate', errorType='noSamplesPerFold') # genesSelected # 2-layer CV repeat 1 inner layer 3 repeat 1: genes Selected getResults(myassessment, c(2,1,3,1), 'genesSelected') # 2-layer CV repeat 1 inner layer 3 repeat 1: genes Selected - fold getResults(myassessment, c(2,1,3,1), 'genesSelected', genesType='fold') # 2-layer CV repeat 1 inner layer 3 repeat 1: genes Selected - model 3 fold 1(twice) getResults(myassessment, c(2,1,3,1), 'genesSelected', genesType='fold')[[3]][[1]] # 2-layer CV repeat 1 inner layer 3 repeat 1: genes Selected frequ - model 3 getResults(myassessment, c(2,1,3,1), 'genesSelected')[[3]] # 2-layer CV repeat 1 inner layer 3 repeat 1: best number of genes getResults(myassessment, c(2,1,3,1), 'bestOptionValue') # 2-layer CV repeat 1 inner layer 3 repeat 1: execution time getResults(myassessment, c(2,1,3,1), 'executionTime')